Lead AI Engineer / Architect - Hybrid ((US Citizens Eligible to Obtain Clearance)

Swingtech•Washington, DC

13d•Hybrid

About The Position

The Lead AI Engineer / Architect will serve as the senior technical authority for an enterprise Artificial Intelligence engineering program. This individual will lead AI solution architecture, engineering direction, hands-on technical delivery, security and compliance alignment, technical quality, and delivery oversight across the full AI system lifecycle. The Lead AI Engineer will establish and maintain architecture standards, reusable engineering patterns, Responsible AI practices, and security controls for enterprise AI solutions, including Generative AI, Large Language Models, Retrieval-Augmented Generation, agentic AI, Model Context Protocol, AI-enabled automation, data pipelines, and MLOps capabilities.

Requirements

At least seven years of hands-on experience in one or more of the following: AI/ML engineering, Enterprise architecture, Cloud engineering, Data engineering, Software engineering
Experience must include direct technical delivery of AI-enabled systems.
At least two years of hands-on experience with one or more of the following: Generative AI, LLM integration, Retrieval-Augmented Generation, Model evaluation, Agentic AI, Production AI systems
Demonstrated experience architecting and delivering secure enterprise or Federal AI solutions.
Experience with AI system architecture, cloud AI platforms, APIs, data pipelines, MCP, vector databases, AI orchestration, model evaluation, and MLOps.
Knowledge of Responsible AI, AI governance, cybersecurity, privacy, accessibility, and Federal compliance requirements.
Demonstrated experience leading Federal ATO activities under NIST SP 800-37 and implementing the FISMA Moderate NIST SP 800-53 control baseline.
Experience designing AI solutions in FedRAMP-authorized environments using a Zero Trust security architecture.
Experience delivering Information and Communication Technology that conforms to Section 508 and WCAG 2.1 Level A and AA.
Experience with AI-specific security and adversarial testing, including prompt injection, jailbreak, data poisoning, and AI red teaming.
Experience leading technical teams and advising Government or enterprise stakeholders.
Must hold at least one relevant AI, Generative AI, machine learning, data engineering, or cloud AI certification.
Must be a U.S. citizen or legal permanent resident.
Must be eligible to obtain and maintain a favorable Tier 1 background investigation, formerly NACI.

Nice To Haves

Certain privileged or higher-risk duties may require a Moderate- or High-Risk background investigation.

Responsibilities

Lead the architecture, design, integration, deployment, enhancement, and technical oversight of secure enterprise AI solutions.
Provide hands-on technical leadership for AI engineering, development, integration, testing, deployment, troubleshooting, and production support.
Define and maintain AI engineering standards, architecture patterns, technical controls, and reusable delivery approaches.
Design and integrate Model Context Protocol, or MCP, server-based components.
Architect governed agentic and multi-agent AI workflows with appropriate human oversight and autonomy controls.
Guide the development of Generative AI, LLM, RAG, advanced RAG, vector search, AI automation, and AI-enabled application capabilities.
Ensure solutions use Government-furnished environments or open, standards-based technologies that do not require separate licensing, purchase, or subscription.
Prepare and support approval requests before introducing models or AI services into the environment.
Oversee AI data architecture, cloud integration, APIs, vector databases, model evaluation, MLOps, monitoring, and operational readiness.
Design and oversee continuous monitoring for model drift, prompt drift, RAG performance, dataset drift, retrieval quality, security threats, and compliance conditions.
Support multimodal AI capabilities involving text, images, audio, video, OCR, and document-layout models when required.
Lead Responsible AI activities, including Responsible AI Impact Assessments, model cards, bias and fairness evaluations, explainability documentation, risk mitigations, and Human-in-the-Loop controls.
Lead technical reviews, architecture decisions, release-readiness reviews, and production-deployment assessments.
Lead Authority to Operate activities under the NIST Risk Management Framework, including security-boundary identification, FISMA Moderate categorization, ATO documentation, assessment support, POA&M management, and significant-change notifications.
Support Section 508 and WCAG 2.1 Level A and AA accessibility compliance.
Serve as an escalation resource for critical production, security, model-quality, and operational incidents.
Provide technical leadership, mentoring, and guidance to engineering and program stakeholders.